Hybrid Raster-Vector Image Processing for Quality and Data Efficiency
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Solution Overview
Problem
Existing image description formats fail to generate images that leverage the advantages of both raster and vector formats, resulting in suboptimal image quality and data efficiency.
Innovation Solution
An information processing apparatus that segments images into raster and vector areas based on object properties, converting between formats as needed to generate hybrid images that combine the strengths of both formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If an image is represented in a single format (raster or vector), then the representation is simple and consistent, but the image quality cannot leverage advantages of both formats simultaneously
Solution Approach 1:
The image is divided into multiple regions, with each region being represented in the most appropriate format (raster or vector) based on its specific characteristics. This segmentation allows different parts of the image to benefit from the strengths of different formats simultaneously, resolving the contradiction between image quality and format flexibility.
Solution Approach 2:
Different regions of the image are assigned different representation formats based on local requirements. Photographic regions use raster format while graphical regions use vector format, allowing each local area to have the quality characteristics it needs without compromising overall image quality or format adaptability.
2Manufacturing precision
If raster format is used for the entire image, then photographic regions maintain good quality, but graphical regions lose scalability and edge quality
Solution Approach 1:
The image is segmented into photographic regions and graphical regions, with each region assigned the appropriate format. This allows photographic regions to maintain quality in raster format while graphical regions retain scalability in vector format, resolving the contradiction between photographic quality and graphical scalability.
Solution Approach 2:
Different format assignments are made based on local region characteristics. Photographic regions are designated for raster format to preserve photographic quality, while graphical regions are designated for vector format to maintain scalability and edge sharpness, thereby resolving the quality-scalability contradiction.
3Stability of the object's composition
If vector format is used for the entire image, then graphical regions maintain scalability, but photographic regions lose quality and detail
Solution Approach 1:
The image is divided into distinct photographic and graphical regions, with format assignment based on region type. This segmentation enables graphical regions to use vector format for scalability while photographic regions use raster format for quality, resolving the contradiction between scalability and photographic quality.
Solution Approach 2:
Format selection is optimized for each local region's requirements. Graphical regions are assigned vector format to preserve scalability and editability, while photographic regions are assigned raster format to maintain photographic quality and detail, thereby resolving the scalability-quality contradiction.
4Ease of manufacture
If image description is done for each object individually in a single format, then processing is simple, but the overall image cannot achieve optimal quality for mixed content
Solution Approach 1:
The image processing is segmented by region type rather than treating the entire image uniformly. Each region is processed independently with the appropriate format, maintaining processing simplicity while achieving optimal overall image quality through differentiated format assignment.
Solution Approach 2:
The processing approach is adapted to local region characteristics, with photographic regions processed as raster and graphical regions processed as vector. This local differentiation maintains ease of processing while significantly improving overall image quality compared to uniform single-format processing.
Data Source
AI summary
An information processing apparatus includes a processor configured to: segment a first image of an object contained in an image into a first area and a second area in accordance with a property of the first image of the object, the first area being to be represented in raster format, the second area being to be represented in vector format; convert an image of the second area into an image in the vector format if the first image of the object is represented in the raster format and convert an image of the first area into an image in the raster format if the first image of the object is represented in the vector format; and generate a second image of the object, the second image containing the image of the first area in the raster format and the image of the second area in the vector format.